The History of Surfactants and Review of Their Allergic and Irritant Properties
Bibliographic record
Abstract
Surfactants, many of which are used as detergents, can be found in many common household items, such as shampoos, conditioners, soaps, and cosmetics. One should recognize the multitude of surfactants that are used in today's products to identify any potential allergic contact dermatitis (ACD) or irritant contact dermatitis (ICD). Given their abundance in everyday products, it is understandable that many cases of occupational contact dermatitis that arise can be attributed to surfactants. The products most connected with ACD are cocamidopropyl betaine, oleamidopropyl dimethylamine, decyl glucoside, 3-dimethylaminopropylamine, amidoamine, and cocamide diethanolamine. Similarly, the most common surfactant-related causes of ICD are sodium lauryl sulfate and benzalkonium chloride. It is important for dermatologists to identify the causes and differentiate between the two, to adjust treatments and products accordingly. Here, the most frequently used surfactants, as well as their correlation between ACD and ICD, will be reviewed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".